What you actually get when you learn here.
Not promises. A clear account of what distinguishes our courses from typical alternatives — so you can decide if this is the right fit for where you are.
Back to HomeSix things that define how we work
These aren't marketing positions. They're the actual characteristics of our courses, each of which we can point to in specific course decisions.
Practitioner instructors
Courses are written and taught by people who work in AI and software development professionally — not only academic researchers or content generalists.
Defined scope per course
Each course covers a specific domain with enough depth to be genuinely useful. We don't try to cover everything lightly — we choose a scope and cover it well.
Written assignment feedback
Assignments are reviewed by instructors and returned with specific written feedback. Not automated grading. Not generic responses.
Honest time estimates
Weekly hour commitments are derived from actual cohort experience and revised after each run. We publish what the work actually takes.
Real-world assignments
Work with actual datasets, realistic codebases, and project briefs drawn from applied AI development scenarios — not contrived classroom exercises.
Asia-first scheduling
Mentor sessions and office hours are scheduled around Bangkok time — ICT (UTC+7) — which aligns naturally with learners across Southeast Asia.
Expertise of the teaching team
Our instructors hold working roles in ML engineering, data architecture, and AI policy research. They write course content based on challenges they've encountered professionally, not from textbooks alone. Assignments are designed around problems that come up in actual AI development work.
When an instructor reviews your assignment, they're drawing on their own experience working with similar problems — which shapes both the quality and the specificity of the feedback you receive.
- Instructors active in AI/ML roles
- Curriculum revised each cohort based on field developments
- Domain-specific knowledge, not general AI overviews
Current tools and approaches
Assignments use current libraries and development environments — the same ones learners will encounter in professional settings. We don't teach deprecated approaches because they're easier to build course material around.
The Recommender Systems course uses public production datasets. The Full-Stack AI programme includes deployment work — not just model training. The Ethics course uses recent case studies drawn from AI development decisions made in the past three years.
- Current Python ML ecosystem throughout
- Real deployment environments in the full-stack programme
- Case studies from recent AI development work
Support during the course
Feedback on assignments is returned within five business days. Learners in the full-stack programme have scheduled one-on-one mentor sessions — not just access to a shared forum. If you're stuck on something specific, there's a person to help you work through it.
Office hours are held during Bangkok business hours. Enquiries sent via email receive a response within one business day. We don't have automated support bots handling learner questions.
- 5-day assignment feedback turnaround
- 1-to-1 mentor sessions in advanced programme
- 1-day email response target
Transparent pricing in Thai Baht
All course fees are listed publicly and denominated in Thai Baht — no currency conversion surprises for learners based in Thailand. There are no hidden fees, add-on modules to unlock content, or upsells after enrolment.
The AI Ethics course at ฿4,200 is among the more accessible entry points for structured, feedback-supported AI learning. The Full-Stack AI programme at ฿35,000 over five months represents the investment required to produce a portfolio-grade AI application — which is the outcome it's designed around.
What you come away with
We're specific about what each course produces. The Ethics course develops analytical frameworks for thinking about AI design decisions. The Recommender Systems course produces a working recommender system in a domain of your choosing. The Full-Stack programme ends with a deployed AI application that can serve as a genuine portfolio piece.
We don't promise career outcomes, salary changes, or employment placement. We describe what the learning produces — and let that speak for itself.
How Garuda Tech compares
A factual comparison between what many AI learning platforms offer and what we do differently.
| Feature | Typical Platforms | Garuda Tech |
|---|---|---|
| Assignment feedback | Automated scoring |
Written instructor feedback |
| Instructor background | Variable |
Active practitioners only |
| Prerequisites stated clearly | Often vague |
Plainly stated per course |
| 1-to-1 mentor access | Rarely included |
Included in advanced programme |
| Time commitment accuracy | Often understated |
Based on actual cohort data |
| THB pricing, no hidden fees | Often USD, add-ons common |
All-inclusive THB fees |
Distinctive aspects of the Garuda Tech approach
Ethics as a core subject — not a module
AI Ethics is a standalone, full course — not a one-hour ethical considerations module tacked onto a technical curriculum. It's taught by a researcher who works on AI governance professionally.
Portfolio project shipped, not submitted
The Full-Stack AI programme culminates in a deployed application — not a notebook or a slide deck. Learners finish with something that runs, not something that was graded.
Structured peer code review
The advanced programme includes a structured peer review process — not just optional discussion boards. Reading and critiquing code thoughtfully is a skill we build deliberately.
Designed around Southeast Asia schedules
Support hours, mentor sessions, and cohort structure are built around ICT (UTC+7) — not repurposed from a Western-market product with inconvenient timing for learners in the region.
Where we are so far
Ready to find the right course?
Tell us where you are in your learning and what you're working toward. We'll help you identify which track fits.